For example i have a set of 9 images from which i am supposed to select the ones containing bridges or traffic lights. If i dont select them all, it wont let me pass. How does it know if we’re training them by completing?
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One way is to apply a controlled experiment method by including a mix of known (control) and unknown (experimental) images. For example, six of the nine images might already be known to contain a bridge.
The system uses your picks on those to decide the probability that you are both [A] a human and [B] OK at picking bridges. It does that based not only on the images you picked, but also other factors such as your IP address, pick speeds, mouse movements, and whatnot.
If those conditions are met, it can assume you more or less picked correctly on the unknown three images. After that they just need to lather, rinse, and repeat the process.
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